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Must-read papers on graph neural networks (GNN)
Perform data science on data that remains in someone else's server
links to conference publications in graph-based deep learning
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
[NeurIPS 2023] LLM-Pruner: On the Structural Pruning of Large Language Models. Support Llama-3/3.1, Llama-2, LLaMA, BLOOM, Vicuna, Baichuan, TinyLlama, etc.
A collection of implementations of deep domain adaptation algorithms
This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.
List of Molecular and Material design using Generative AI and Deep Learning
Explore a comprehensive collection of resources, tutorials, papers, tools, and best practices for fine-tuning Large Language Models (LLMs). Perfect for ML practitioners and researchers!
A Survey on Multimodal Retrieval-Augmented Generation
[Arxiv] Discrete Diffusion in Large Language and Multimodal Models: A Survey
An Open-Source Toolkit for Heterogeneous Information Network Embedding (HINE)
List of molecules (small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dynamics (force fields) using generative artificial intelligence and deep learning
An automated scoring function to facilitate and standardize the evaluation of goal-directed generative models for de novo molecular design
[NeurIPS 2022] A Fast Post-Training Pruning Framework for Transformers
A collection of graph foundation models including papers, codes, and datasets.
Codebase and CLI for PLAPT: A state-of-the-art protein-ligand binding affinity model for drug discovery
Repository for SMILES-based RNNs for reinforcement learning-based de novo molecule generation
A curated list of papers related to molecular diffusion models.
Ying Nian Wu's UCLA Statistical Machine Learning Tutorial on generative modeling.
Token-Mol 1.0：tokenized drug design with large language model
a Large-Scale Multi-Modal Dataset Containing 20 Million Descriptions